Need helps on how to build a pandas dataframe including these items from listing.

[Mark00353]

Hi, I am a green hand here, and thanks a million for the daftlistings codes:

for listing in listings:
print(listing.publish_date)
print(listing.title)
print(listing.price)

I attempted to list these items into a pandas dataframe layout and export the results into an excel format, somehow I failed to do so, Can anyone helps me on this matter?

Thanks again.

[sdfordham]

If you want something openable with excel, then use the csv package from the standard library. Make sure to open with encoding='utf-8' or the euro symbol will get mangled.

import csv
from daftlistings import Daft, Location, SearchType, PropertyType

daft = Daft()
daft.set_location(Location.DUBLIN)
daft.set_search_type(SearchType.RESIDENTIAL_RENT)
daft.set_property_type(PropertyType.APARTMENT)
daft.set_max_price(700)

listings = daft.search()

with open('./listings.csv', 'w', newline='', encoding='utf-8') as F:
    writer = csv.writer(F)
    writer.writerow(['title', 'price', 'link']) # Column names
    for listing in listings:
        writer.writerow([listing.title, listing.price, listing.daft_link])

If you really want the listings in a pandas.DataFrame then there are many ways to skin this cat, I prefer to create from a dictionary.

import pandas as pd
from daftlistings import Daft, Location, SearchType, PropertyType

daft = Daft()
daft.set_location(Location.DUBLIN)
daft.set_search_type(SearchType.RESIDENTIAL_RENT)
daft.set_property_type(PropertyType.APARTMENT)
daft.set_max_price(700)

listings = daft.search()

# Convert to a list of dictionaries
listings = [
    {'title': listing.title,
     'price': listing.price,
     'link': listing.daft_link} for listing in listings
]
df = pd.DataFrame.from_dict(listings)
print(df)

[Mark00353]

Thanks a million Sir!

Both options you mentioned at above are extremely helpful, I needed to build the the dataframe for plotting (like matplotlib) and also needed them in CSV format to play around with them.

Thanks again.